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The Power of Anonymization and Sensitive Knowledge Hiding Using Sanitization Approach
Author(s) -
T. Satyanarayana Murthy,
N.P. Gopalan,
Datta Sai Krishna Alla
Publication year - 2018
Publication title -
international journal of modern education and computer science
Language(s) - English
Resource type - Journals
eISSN - 2075-017X
pISSN - 2075-0161
DOI - 10.5815/ijmecs.2018.09.04
Subject(s) - computer science , database transaction , set (abstract data type) , information sensitivity , transaction data , data mining , information hiding , association rule learning , anonymity , database , computer security , artificial intelligence , embedding , programming language
In recent day’s huge rapid growth of corporate industries professional are based on the online marketing. These markets are associated with millions of online transactions which contain the details of the items, number of items, price and additional information like working details, salary information and personal information. The customers associated with these transactions are concerned about privacy issues. This manuscript aims to concentrates more on the additional information about the customer apart from dealing with the items. More analysis helps in knowing the sensitive information about an individual. In this article two algorithms were used, out of which first algorithm has been used to hide the sensitive information about an individual and other proposed algorithm has been used to hide the sensitive transaction information. These algorithms are proposed based on k-Anonymity and association rule hiding techniques. A novel algorithm has been proposed for association rule hiding algorithm to reduce the side effects such as Sensitive item-set hiding failure, Non-sensitive misses, extra item-set generations and Database dissimilarities along with the reduction of running time and complexities through transaction deletion.

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